EVALUATING MILITARY INSTALLATION OPERATIONS DEPENDENCE ON INFRASTRUCTURE USING MACHINE LEARNING AND SURVEY DATA

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dc.contributor.advisorReilly, Allison Cen_US
dc.contributor.authorMagoulick, Paul Fen_US
dc.contributor.departmentCivil Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2021-09-17T05:38:19Z
dc.date.available2021-09-17T05:38:19Z
dc.date.issued2021en_US
dc.description.abstractCritical infrastructure on many Department of Defense (DOD) installations are increasingly threatened by extreme weather, in part due to climate change and also in part due to the location vulnerability of these assets. At the same time, they are being relied upon more to ensure overall mission success. While each installation has its unique mission, we explore the mission at one installation – marine recruit training at the U.S. Marine Corps Recruit Depot in Parris Island, South Carolina – and predict how day-to-day and extreme weather events lead to infrastructure failures through statistical modeling. We then quantify what this means for installation operability by surveying individuals tasked with mission training. The results are informative for how to allocate resources for infrastructure enhancements in a way that protects base operability in addition to base infrastructure.en_US
dc.identifierhttps://doi.org/10.13016/jae0-hazy
dc.identifier.urihttp://hdl.handle.net/1903/27837
dc.language.isoenen_US
dc.subject.pqcontrolledCivil engineeringen_US
dc.subject.pquncontrolledelectrical outagesen_US
dc.subject.pquncontrolledmachine learningen_US
dc.subject.pquncontrolledmilitary installationsen_US
dc.subject.pquncontrolledprediction modelsen_US
dc.titleEVALUATING MILITARY INSTALLATION OPERATIONS DEPENDENCE ON INFRASTRUCTURE USING MACHINE LEARNING AND SURVEY DATAen_US
dc.typeDissertationen_US

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